Why use CIFTI files?
Advantages of surface-based analyses for cortical gray matter (Fischl et al., 1999; Anticevic et al., 2008; Van Essen, 2012; Glasser et al., 2016; Coalson et al., 2018; Brodoehl et al., 2020)
More appropriate smoothing
More accurate spatial modeling
Better inter-subject alignment
Reduced dimensionality
Doesn’t omit the subcortex
Why bother converting volumetric fMRI data to a surface format? First, smoothing and spatial modeling can take advantage of more accurate distances between brain locations. Since the cortical sheet is folded, two locations on adjacent folds may be quite close in Euclidean space, but actually far on the cortical surface. Surface-based analyses will measure the correct distance along the surface, so that more distal regions aren’t improperly treated together. And because cortical folding varies between individuals, inter-subject alignment is improved with surface data, leading to increased sensitivity and specificity in group analyses. Finally, the data is of reduced dimensionality, which helps make intensive strategies like Bayesian modeling more feasible. And the reason you’d want to use a CIFTI file instead of GIFTI files is for inclusion of the subcortex. There’s also the benefit of containing both hemispheres in a single file, whereas GIFTI files have separate files for the left and right cortex.
